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Power of Data Science in five points

Data Science is the busiest buzzword of the 21st century. Every technologist is obsessed with it and there are vital reasons for it. From entertainment to healthcare, every industry has seen a surge of data science in their day-to-day operations to make life much better and processes much easier for human resources. Let’s try to break understanding power of data science into 5 points –

  1. A concoction – Data science is the perfect blend of Statistics, Computer Science, and information management. We can derive various information from data and that is what we have been doing for a long time but when that information is validated with the use of principles of statistics, information transforms into knowledge. Computer science makes processes easier and computation faster which helps various industries use powerful systems (machines) to form knowledge from pieces of information with the help of Data.

 

  1. Industry Agnostic – Data science is the study of data with the help of statistics. Going with this definition, any field which generates data or has the potential to generate data can have a meaningful application of Data Science.

 

  1. Mathematic Driven – Often we see data science as a black box where users don’t know what is happening behind the scenes and still they believe the information provided by data science algorithms. This is not true at all, every algorithm is an algorithm because it has logic behind the scene. And prolonged learning of algorithms makes machines make complex decisions easier. 

 

  1. Data Foundation – Data serves as the foundation for data science, this essentially means that all algorithms which work learn from user-generated data. These algorithms learn the behavior of data that is true to users, that is why the results produced by these algorithms are close to reality. 


Trusting Data Science – When we write algorithms, we make various safety valves to prevent algorithms from behaving oddly. It means if data is bad, an algorithm might not always be bad because it learns from various sets of data and makes decisions based on weights provided by humans and safety valves that prevent it from going south. So if you think people can fool these algorithms, it is really hard to beat this system.

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